Gimenez Olivier, Covas Rita, Brown Charles R, Anderson Mark D, Brown Mary Bomberger, Lenormand Thomas
Institute of Mathematics, Statistics and Actuarial Sciences, University of Kent, Canterbury, England.
Evolution. 2006 Mar;60(3):460-6.
Assessing natural selection on a phenotypic trait in wild populations is of primary importance for evolutionary ecologists. To cope with the imperfect detection of individuals inherent to monitoring in the wild, we develop a nonparametric method for evaluating the form of natural selection on a quantitative trait using mark-recapture data. Our approach uses penalized splines to achieve flexibility in exploring the form of natural selection by avoiding the need to specify an a priori parametric function. If needed, it can help in suggesting a new parametric model. We employ Markov chain Monte Carlo sampling in a Bayesian framework to estimate model parameters. We illustrate our approach using data for a wild population of sociable weavers (Philetairus socius) to investigate survival in relation to body mass. In agreement with previous parametric analyses, we found that lighter individuals showed a reduction in survival. However, the survival function was not symmetric, indicating that body mass might not be under stabilizing selection as suggested previously.
评估野生种群中表型性状上的自然选择对进化生态学家来说至关重要。为了应对野外监测中个体检测不完美的问题，我们开发了一种非参数方法，用于使用标记重捕数据评估数量性状上自然选择的形式。我们的方法使用惩罚样条来灵活探索自然选择的形式，避免了事先指定参数函数的需要。如果需要，它可以帮助提出新的参数模型。我们在贝叶斯框架中采用马尔可夫链蒙特卡罗抽样来估计模型参数。我们用群居织巢鸟（Philetairus socius）野生种群的数据来说明我们的方法，以研究与体重相关的生存情况。与之前的参数分析一致，我们发现较轻的个体生存几率降低。然而，生存函数不对称，这表明体重可能不像之前所认为的那样处于稳定选择之下。
